Administrators of modem computing systems generally have various parameters available that can be adjusted or configured to values that result in improved performance of the system. Size of swap space, memory dedicated to buffer-cache, maximum number of processes permitted, and maximum application data size are examples of such parameters that could be so adjusted.
With limited success, various techniques have been used to make these parameter adjustments. One common solution to this problem is for the administrator or operator to learn the details of the inner workings or operation of each application, and then speculate as to the optimal configuration of the computer system. This approach has several disadvantages: (1) it is extremely time consuming, especially since it must be repeated as each new application or workload is brought into the system, (2) there is frequently insufficient data available from the vendor of the applications to do this with any precision, (3) it is an error prone process as there are often unforseen dependencies which makes such speculation highly inaccurate, and (4) optimal system parameter values can be dependent upon application usage characteristics, which can vary from time to time.
Another solution to this problem is to build a separate mechanism for each system parameter which influences system performance and which can be adjusted. Each such mechanism would have the capability of measuring system metrics and evaluating whether or not a change in the parameter controlled by that mechanism is called for. For example, such a mechanism could control a system's virtual memory and could detect when the system either has or is in danger of running out of virtual memory. The mechanism could then recommend that the system be reconfigured to increase virtual memory. One problem with this approach is that a separate mechanism must be created for each system parameter that it is desirable to control.
Thus, there is a need for a method by which a computer system can be more effectively and efficiently improved. In particular, there is a need for a method to automatically and continually adjust system parameters to obtain improved system performance, even as the workload on the system changes.